Existing machine translation systems produce translations in a variety of languages. Although many such translation systems leverage scale to provide high-quality translations, they provide only limited opportunities to customize translations or preserve customer-specific terminology and branding. Users of such systems may not be able to prevent, for example, the translation of brand names, or be able to customize the translation of difficult-to-translate phrases such as specialty terminology and idioms, that tend to be rich in metaphors and cultural nuances. As a result of these limitations, existing translation systems often produce the somewhat awkward or terminologically inaccurate translations that have come to be associated with machine translation.
Moreover, as existing translation systems are generally trained on text that is accurately spelled and grammatically sound, they are ill-equipped to translate text generated from the use of informal, real-time modes of communication such as Short Message Service (SMS) or Instant Message (IM). Consequently, when these systems encounter the inherently imprecise text resulting from such communications, they often produce translations that are replete with errors. These translation errors occur at least because machine translation systems are not presently designed to handle the use of slang, abbreviations, and non-standard punctuation, spelling, and grammar, commonly found in text resulting from real-time modes of communication.
Existing machine translation systems also present security challenges when used to translate information of a proprietary or sensitive nature. For example, by transmitting sensitive content over insecure communication channels, present systems routinely risk exposing such content to unintended parties. Some translation systems also transmit content to third-party translation providers or engines without retaining control over the provider's further use or dissemination of the transmitted content. As a result, once an end-user provides such systems with translation content that includes sensitive information such as credit card numbers, there is no guarantee that the information will not be made available to other parties or otherwise inappropriately used during or even after the end of the translation transaction.
Although some specialty translation systems attempt to provide some degree of customization and security, they nevertheless exhibit the drawbacks noted above, and are generally only able to support translation between a select few languages. Accordingly, there is a need in the art to develop machine translation methods and systems that overcome at least the above-identified limitations of prior art systems, and provide high-quality machine translations under a variety of use-conditions.